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Business Problem User queries cannot be answered satisfactorily using a single source. We can use a very effective technique called RAG( Retrieval Augmented Generation) for getting the results from a rich context and sending it to a LLM( Large Langua...
Business Requirement I am a student and I want answers from my textbooks easily so that I can understand the subject better. Goal Understand Vector Database Understand RAG Understand how to product
From the TensorFlow documentation word embeddings documentation Word embeddings give us a way to use an efficient, dense representation in which similar words have a similar encoding. Importantly, you do not have to specify this encoding by hand. An...
Hackathons and Community Building
In this blog, we would be doing question and answering on a news data feed. The blog has 2 parts Conceptual Implementation details which comes as expected with code as well as the full code link Please feel free to choose both or at lea...
RAG [ Retrieval-Augmented Generation ] with AWS Bedrock and Qdrant in 8 minutes https://youtu.be/DIWYqTj4vj0
Overview The session gives an overview of Azure AI and the position of Azure OpenAI in the Azure AI ecosystem. We focus on a question and answering system and show the different components of the built question answering system ✅ Header ✅ Context ✅ P...